Fwd: [NumFOCUS Projects] Round 1 Small Development Grants CFP is open

[Francesc Alted]

FYI

---------- Forwarded message ---------
De: Nicole Foster <nic...@numfocus.org>
Date: dv., 5 febr. 2021, 22.12
Subject: [NumFOCUS Projects] Round 1 Small Development Grants CFP is open
To: Fiscally Sponsored Project Representatives <proj...@numfocus.org>, Affiliated Projects <affil...@numfocus.org>

Hello Projects!

NumFOCUS is pleased to invite proposals for our 1st round of Small Development Grants for 2021!

Apply Here: https://numfocus.typeform.com/to/mbtH7w

Timeline:

• Deadline for Proposal Submission: March 5, 2021

• Projects will be Notified: April 15, 2021 (or sooner)

Available Funding:

• Up to $5,000 per proposal

Eligibility:

• Any NumFOCUS Fiscally Sponsored or Affiliated project may submit 1 proposal on behalf of the project per grant cycle.

• If you wish to solicit proposal ideas from your project community, the project leaders must organize their own review process to select the proposal that the leadership will put forward to NumFOCUS.

• Funding can be used for: code development; documentation work; website updates; workshops and sprints; educational, sustainability, and diversity initiatives; or other types of projects.

• Proposed work must be achievable within the 12 months following the award.

• The call is open to applicants from any nationality and can be performed at any university, institute, or business worldwide (US export laws permitting).

Funding Distribution:

• For fiscally sponsored projects only, NumFOCUS can deposit the grant funding directly into the project’s account. The project would then submit invoices through the normal channels (i.e. Rocket) to pay the grant expenses.
• NumFOCUS can set up an independent contractor agreement with an individual or company.
• NumFOCUS can award the money as a grant or subcontract to a student or postdoc at a university (depending on the rules of the university).
• NumFOCUS can directly pay for expenses associated with the grant (e.g. booking flights on behalf of project leaders to attend a workshop, per diems for travel days)

You can see past successful proposals here: https://numfocus.org/programs/sustainability#sdg

Please feel free to reach out if you have any questions.

--

Nicole Foster

Operations Manager, NumFOCUS

nic...@numfocus.org

512-831-2870 x102

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[Miroslav Šedivý]

Thank you, Francesc, for the forwarded message.

When checking the linked NumFOCUS page, PyTables has obtained two
grants until now:

2017: h5py backend for PyTables
2018: Better support for native HDF5 files

What are our options this year? I'd like to hear your ideas and
opinions.

As a new maintainer, I have started with a few ideas that should improve
the quality of the codebase and attractivity of the repository, but now
I do not have as much time as I had in December/January:

- modernization of the code (Python 3.6+), removal of old hacks
- better tests, preferably in pytest format
- cleanup and extraction of dependencies
- cleanup in bench/contrib/examples (bench could run as benchmarked
tests)
- (and of course taking care of all reported issues from the users and
new features)

This is a bunch of work that does not have to be done quickly, so I can
do it with your assistance from time to time. But if there should be
some paid position, I wouldn't be able to manage it the whole time.

There's however, a huge “heavy” test suite. And there's this warning:

The whole suite will take more than 4 hours to complete on a
relatively modern CPU and around 512 MB of main memory.

I'm afraid of starting this on my “relatively modern” laptop, but since
it has 16 times more memory, I suspect that this message is so old,
that those 4 hours would be probably much less. Nevertheless having the
possibility of *quick* testing of everything, would allow me to try
more stuff easily without breaking the project. And if we want to
convert the tests to pytest, then having a high-performance test system
would be a good help on that way. After that I believe, that our tests
could be much better customizable for future development, which would
attract the new contributors.

Therefore my proposal for 2021, when we cannot travel to meet and speak
to the (potential) users anyway, would be on the hardware side.

Or is my problem fixable with some simple hack in the
`.github/workflows/*.yml` files that would allow faster parallelized CI
runs?

Anyway I am looking forward to your ideas!

Miro

[Francesc Alted]

Hey Miro,

Missatge de Miroslav Šedivý <mi...@sedivy.de> del dia dv., 19 de febr.
2021 a les 21:34:

>
> Thank you, Francesc, for the forwarded message.
>
> When checking the linked NumFOCUS page, PyTables has obtained two
> grants until now:
>
> 2017: h5py backend for PyTables
> 2018: Better support for native HDF5 files

Yeh, I almost forgot about them. While the first grant was not
successful (integrating h5py as a backend ended requiring much more
work than we initially realized), the second one was completed (IIRC).

<snip>

> There's however, a huge “heavy” test suite. And there's this warning:
>
> The whole suite will take more than 4 hours to complete on a
> relatively modern CPU and around 512 MB of main memory.
>
> I'm afraid of starting this on my “relatively modern” laptop, but since
> it has 16 times more memory, I suspect that this message is so old,
> that those 4 hours would be probably much less. Nevertheless having the
> possibility of *quick* testing of everything, would allow me to try
> more stuff easily without breaking the project. And if we want to
> convert the tests to pytest, then having a high-performance test system
> would be a good help on that way. After that I believe, that our tests
> could be much better customizable for future development, which would
> attract the new contributors.

Regarding this point, IIRC the heavy test suite was mainly meant to
test the indexing engine in PyTables. This engine is quite complex,
and has several optimizations for large tables, and this is mostly why
the tests require that long. In general, if you don't touch the
indexing engine, you don't need to re-run the heavy tests (although it
is always nice to run it at least once before a release). Regarding
the required time, yeah, that statement was written circa 2007, so it
is probably much less now (hopefully :-).

--
Francesc Alted